With the rapid development of image processing technologies in recent years, automatic image tracking technologies have also become sophisticated. However, the accuracy of tracking an object in a video still need be improved. For example, the pre-existing tracking algorithms usually have a specific searching range, so when an object in a video moves by an excessive displacement amount or at a very fast speed, it is likely that the object will disappear from the frame or temporarily disappear from and then comes back to the frame. As a consequence, the tracked object goes beyond the specific searching range of the tracking algorithms to make it impossible to accomplish tracking of the object. Additionally, when there are objects similar to the tracked object in the video, the current tracking technologies often fail to distinguish between them, thus leading to false tracking results.
Accordingly, there is an urgent need in the art for a technology that can accurately identify and track an object without consuming a lot of computing resources so as to avoid the problem that the object going beyond the specific searching range cannot be tracked and avoid the shortcoming that false tracking results may be caused due to objects similar to the tracked object.